Kim, Chung-Soo;Jo, Young-Jun;Park, Se-Ho;Kim, Hae-Jung;Han, Jin-Yi;Hong, Jin-Tae;Cheong, Jae-Hoon;Oh, Ki-Wan
Biomolecules & Therapeutics
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v.18
no.2
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pp.219-225
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2010
We tested whether ginsenosides $Rg_3$-standardized ginseng extract (RGE) has anti-stress effects in restraint-stressed animals. RGE increased time spent in the open arms and open arm entries in the elevated plus-maze test. In addition, RGE blocked the reduction of center zone distance and stereotypes behaviors in the open-field test. RGE also increased head dips in stressed mice, indicating anxiolytic-like effects. Stress decreased movement distance and duration, burrowing, and rearing frequency but increased face washing and grooming. RGE significantly reversed burrowing and rearing activity in stressed mice. In addition, we measured sleep architecture in restraint stressed rats using EEG recorder. Stress increased rapid eye movement (REM) sleep, but total sleep and non-rapid eye movement (NREM) sleep were not changed. RGE did not affect sleep architecture in stressed rats. These behavioral experiments suggest that RGE has anti-stress effects in restraint-stressed animal models.
Journal of the Institute of Electronics and Information Engineers
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v.50
no.10
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pp.207-216
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2013
The aim of this study is to design a classifier for sleep stage analysis and select important feature set which shows sleep stage well based on physiological signals during sleep. Sleep has a significant effect on the quality of human life. When people undergo lack of sleep or sleep-related disease, they are likely to reduced concentration and cognitive impairment affects, etc. Therefore, there are a lot of research to analyze sleep stage. In this study, after acquisition physiological signals during sleep, we do pre-processing such as filtering for extracting features. The features are used input for the new combination algorithm using genetic algorithm(GA) and neural networks(NN). The algorithm selects features which have high weights to classify sleep stage. As the result of this study, accuracy of the algorithm is up to 90.26% with electroencephalography(EEG) signal and electrocardiography(ECG) signal, and selecting features are alpha and delta frequency band power of EEG signal and standard deviation of all normal RR intervals(SDNN) of ECG signal. We checked the selected features are well shown that they have important information to classify sleep stage as doing repeating the algorithm. This research could use for not only diagnose disease related to sleep but also make a guideline of sleep stage analysis.
Background : It is well known that non-rapid eye movement(NREM) sleep activates the occurrence of interictal epileptiform discharges(IED) in many epileptic syndromes. We performed this study to assess the effect of NREM sleep on IED in epileptic patients with organic brain lesions. Materials and Methods : We analyzed awake and sleep electroencephalopathy(EEG) recorded simultaneously after partial sleep deprivation in 50 patients. We calculated the awake and sleep spike index (ASI and SSI, spikes/epoch), and the percentage increase of ASI and SSI during sleep. Results : In the 50 patients, the IEDs were recorded exclusively during the awake state in 1 (2%) patient, and during the sleep state in 13(26%) patients. The SSI was higher in 44 (88%) patients, and the ASI was higher in 5 (10%) patients. The mean ASI and the SSI in patients with organic brain lesions were $0.058{\pm}0.121$ and $0.148{\pm}0.187$, and it was $0.081{\pm}0.150$ and $0.174{\pm}0.226$ in patients without organic brain lesions. There were significant increases in the spike index (P<0.05) during NREM sleep in both groups (n=36), but no significant difference in the percent increase of spike index (P>0.05). Conclusion : The IEDs were activated significantly during NREM sleep both in patients with and without organic brain lesions, but there were no differences in the degree of activation in both groups. The activating effect of NREM sleep was not correlated with clinical factors such as, frequent nocturnal seizures, frequent generalized tonic clonic seizures, type of epilepsy and taking anticonvulsants. We conclude that the routine EEG used to evaluate epileptiform discharges in epileptic patients should include sleep recordings after partial sleep deprivation.
Proceedings of the Korean Society for Emotion and Sensibility Conference
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2002.05a
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pp.181-185
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2002
The purpose of this study was to find out the relationship between sleep physiological signals data and subjective feeling of sleep quality. Sixteen subjective were investigated and they slept on both comfortable mattress and uncomfortable mattress. Information of sleep stage is one of the most important clues for sleep quality. Polysomnography is basically the recording of sleep. The several channels of brain waves (EEG), eyes (EOG), chin movements (EMG) and heart (ECG) were monitored. Sixteen subjects spent 6 days and nights in the laboratory and the data of sleeping 7h for each of 3 nights was analyzed. Percentage of deep sleep (III and IV, sleep efficiency, WASO, stage 1 and subjective feeling of sleep quality were significantly affected with mattress types (comfortable and uncomfortable mattress). When subjects slept on comfortable beds, percentage of deep sleep and sleep efficiency were higher than those of uncomfortable bed. The percentages of wake after sleep onset and stage 1 were lower when subject slept in a comfortable bed. The subjective feeling of sleep quality agreed with the recorded sleep data also.
We studied the effects of acetylcholinesterase inhibitors, donepezil and galantamine, and an N-methyl-D-aspartate (NMDA) receptor blocker, memantine, on sleep-wake architecture in rats. Screw electrodes were chronically implanted into the frontal and parietal cortex for the electroencephalography (EEG). EEG was recorded with a bio-potential amplifier for 8 h from 09:30 to 17:30. Vibration was recorded to monitor animal activity with a vibration measuring device. Sleep-wake states such as wake (W), slow-wave sleep (S) and paradoxical or rapid eye movement sleep (P), were scored every 10 sec by an experimenter. We measured mean episode duration and number of episode to determine which factor sleep disturbance was attributed to. Donepezil and memantine showed a significant increase in total W duration and decreases in total S and P duration and delta activity. Memantine showed increases in sleep latency and motor activity. Changes of S and P duration in memantine were attributed from changes of mean episode duration. Galantamine had little effect on sleep architecture. From these results, it is showed that galantamine may be an anti-dementia drug that does not cause sleep disturbances and memantine may be a drug that causes severe sleep disturbance.
This study investigated the effects of Origanum majorana essential aroma therapy on electrical activity in the brain as evaluated by an electroencephalogram (EEG). The subjects were 29 healthy female young adults, and their sleep quality was assessed by using the Pittsburgh Sleep Quality Index. EEG electrodes were attached at the frontal, temporal, occipital, and parietal lobes according to the international 10-20 system. Subjects were exposed to organic Origanum majorana essential aroma (50 ${\mu}l$) for a period of 3 minutes each before, during, and after aromatherapy. Subjects with good sleep quality showed that Origanum majorana essential aroma increased the theta power at the frontal and temporal lobes of both cerebral hemispheres, the left parietal lobe, and the right occipital lobe. Furthermore, Origanum majorana essential aroma decreased the alpha power at the left occipital lobe and the beta power at the right temporal lobe. On the other hand, subjects with poor sleep quality showed an increase in the theta power at the temporal lobe of both cerebral hemispheres and a decrease in the alpha power at the left parietal lobe by Origanum majorana essential aroma therapy. It is concluded that Origanum majorana essential aroma therapy diminishes the state of wakefulness in the brain; alpha and beta powers were both decreased in the subjects with good sleep quality, but only alpha power was decreased in the subjects with poor sleep quality. Moreover, Origanum majorana essential aroma therapy has a sleep-inducing effect in both subjects with good sleep quality and poor sleep quality.
The Journal of Korean society of community based occupational therapy
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v.8
no.2
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pp.29-37
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2018
Objective : Sleep disorder caused by stress or disease to elderly currently. We tried to make clear constant exercise according to exercise intensity would have effect on sleep disorder in elderly using EEG and melatonin. Methods : Thirty subjects were over 65 years old who lived a senior facility in some parts. They were able to communicate and understand the purpose of the study. They also expressed their intension to participate actively in experiment. They should have alert consciousness and orientation about time, place, and people. Sleep disorder was assessed via below 6 hr total sleep time and Pittsburge Sleep Quality Index, which was satisfied with both of criterion at the same time. Exercises composed of low intensity walking, moderate aerobic exercise, and high intensity resistance strength. We used QEEG 8-System (LAXTHA Inc. KOREA) to check wave type and Polysomnograpy (Compumedics, Australia) to test quality of sleep. and Histologic features were observed by TTC (triphenyltetrazolium chloride) staining and H & E (Hematoxylin & Eosin) staining. Results : There was a significant sleep index and change of melatonin after aerobic exercise. There was a significant SOL, S1, S2, and SWS in aerobic exercise, but there was a significant SWS in walking and resistance strength. There was a significant change of delta wave especially in frontal and temporal region between exercises. Conclusion : They had different effects according to type of exercise, when elderly who have chemical, behavioral change of circadian rhythms did exercise consistently. Aerobic exercise had more effect on sleep disorder than other exercise. Therefore, we may supply proper exercise to elderly and high quality of life.
Transactions on Control, Automation and Systems Engineering
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v.4
no.3
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pp.239-243
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2002
Multi-valued decision making for transitional stochastic events was newly derived based on conditional probability of knowledge database which included experts'knowledge and experience. The proposed multi-valued decision making was successfully adopted to the determination of the five levels of the vigilance of a subject during the EEG (electroencephalogram) recording; awake stage (stage W), and sleep stages (stage REM (rapid eye movement), stage 1, stage 2, stage $\sfrac{3}{4}$). Innovative feature of the proposed method is that the algorithm of decision making can be constructed only by use of the knowledge database, inspected by experts. The proposed multi-valued decision making with a mathematical background of the probability can also be applicable widely, in industries and in other medical fields for purposes of the multi-valued decision making.
Objectives: Stage 1 sleep provides important information regarding interpretation of nocturnal polysomnography, particularly sleep onset. It is a short transition period from wakeful consciousness to sleep. The lack of prominent sleep events characterizing stage 1 sleep is a major obstacle in automatic sleep stage scoring. In this study, utilization of simultaneous EEG and EOG processing and analyses to detect stage 1 sleep automatically were attempted. Methods: Relative powers of the alpha waves and the theta waves were calculated from spectral estimation. A relative power of alpha waves less than 50% or relative power of theta waves more than 23% was regarded as stage 1 sleep. SEM(slow eye movement) was defined as the duration of both-eye movement ranging from 1.5 to 4 seconds, and was also regarded as stage 1 sleep. If one of these three criteria was met, the epoch was regarded as stage 1 sleep. Results were compared to the manual rating results done by two polysomnography experts. Results: A total of 169 epochs were analyzed. The agreement rate for stage 1 sleep between automatic detection and manual scoring was 79.3% and Cohen’s Kappa was 0.586 (p<0.01). A significant portion (32%) of automatically detected stage 1 sleep included SEM. Conclusion: Generally, digitally-scored sleep staging shows accuracy up to 70%. Considering potential difficulty in stage 1 sleep scoring, accuracy of 79.3% in this study seems to be strong enough. Simultaneous analysis of EOG differentiates this study from previous ones which mainly depended on EEG analysis. The issue of close relationship between SEM and stage 1 sleep raised by Kinnari remains a valid one in this study.
Objectives The eye movement (EM) has been reported to play a role in enhancing the retrieval of episodic memories and reducing effects of fearful episodes in the past and worries for the futures. However, it is still unclear in the mechanism of EM in normal subjects. We examined the horizontal eye movement (HEM) effect using an aiding apparatus on mental health indices including negative and positive psychological factors, and psychophysiological measures such as heart rate variability and quantitative electroencepaholography (qEEG) in healthy subjects. Methods Twenty eight healthy subjects were recruited and randomly allocated into two groups : active HEM group and control group. The active HEM group conducted the HEM training with usual stress management audio-intervention using the apparatus inducing eye movement once a day for 14 days. The control group also conducted the same training once a day for 14 days, however, the saccadic eye movement was not included in this training. Psychological measurements, neurocognitive function tests, heart rate variability measurement and qEEG were conducted before and after the training in both groups. Results In the active HEM group, sleep status using Sleep Quality Scale (SQS) positive factors significantly increased after the training. By contrast, scores on the negative items of Psychological Well-Being Scale (PWBS), and negative items of the Life Orientation Test-Revised (LOT-R) were significantly decreased after the training. The percentage of delta amplitude (1-3 Hz) in qEEG significantly decreased after the HEM training. The percentage of alpha amplitude (8-12 Hz) significantly increased after HEM training. The change of delta amplitude in the active HEM group was positively correlated with the change of sleep satisfaction of Visual Analogue Scale (VAS), and the change of alpha amplitude was negatively correlated with depression of VAS, anxiety of VAS and Beck Anxiety Inventory (BAI). Conclusions The HEM training improved sleep quality and well-being, and sense of optimism. The HEM training also increased alpha amplitude and decreased delta amplitude in qEEG. The qEEG changes were well correlated with subjective improvement of mental health indices in healthy subjects. These results suggest some evidences that HEM training using the apparatus that induces EM would be helpful in improving subjective mental health in healthy subjects. Further study with larger samples size would be needed.
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